ML-powered predictive scoring

Built specifically for your affiliate program

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Act with confidence. Scale with clarity.

Most Affiliate Teams are Still Fly Half-Blind

Hidden Value

Partner value is buried in analytics — getting it means chasing reports, syncing data, waiting on people.

Delayed Clarity

Marketing metrics (CTR, CR, ROI) don’t give you instant clarity on long-term value.

Missed Growth

As a result, we keep paying for underperforming campaigns longer than we should — while missing the window to scale the ones that actually work.

Custom Affiliate Intelligence

In just 4 simple steps

KPI definition

Before we start collecting data, we work with you directly to define your objective. Whether it’s ROI prediction, traffic scoring, or conversion forecasting — we’ll help you clarify the most impactful insight for your Affiliate program.

Integration setup

No technical stress. Just guided integration. We adapt to your platform, help you structure the right data, and walk you through every step.

Custom learning

Once we have enough signals, we train a lightweight model to score future partners — ranking with defined metrics.

Get the insight and Act

Use model outputs directly in your workflow:

Adjust rates
Flag risky partners
Scale high-potential ones earlier
All backed by live predictions

How it works

Level 1: Input

Level 2: Prediction core

Level 3: Output & Action

Level 1: Input

Step 1 — Integration & Setup: Affiliate platform integration (e.g., Affise, Everflow):

API access to campaign data: clickid, aff_id, clicks, conversions, payouts, EPC, CR, etc.

Frontend tracking script installation:

Lightweight JS script embedded via GTM or manually.
Collects user behaviour (scrolls, clicks, time on site, form submits)
Attributes each session to clickID.

Step 2 — Local Data Aggregation:

Match behavioral events with affiliate traffic via clickid.

Compute session-level features:

avg_time_on_site, scroll_depth, engagement_score, etc.
Format the feature set for secure inference.

Level 2: Prediction core

Step 3 — Secure ML Prediction:

Deploy a lightweight inference agent inside a secure enclave (e.g. Intel SGX, AWS Nitro).
Input: aggregated behavioral + campaign data (from Step 2).
Model executes privately — no access to raw data or model weights.

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Level 3: Output & Action

Step 4 — Sync & Visual:

Prediction results are: